358 results about "Context model" patented technology

A video frame arithmetical context adaptive encoding and decoding scheme is presented which is based on the finding, that, for sake of a better definition of neighborhood between blocks of picture samples, i.e. the neighboring block which the syntax element to be coded or decoded relates to and the current block based on the attribute of which the assignment of a context model is conducted, and when the neighboring block lies beyond the borders or circumference of the current macroblock containing the current block, it is important to make the determination of the macroblock containing the neighboring block dependent upon as to whether the current macroblock pair region containing the current block is of a first or a second distribution type, i.e., frame or field coded.

A method of video encoding is provided that includes performing context-adaptive binary arithmetic coding (CABAC) on a plurality of syntax element values in a slice to generate a plurality of entropy-encoded syntax element values, generating an entropy slice header to identify the plurality of entropy-encoded syntax element values as an entropy slice, wherein the entropy slice header comprises context model initialization information, and outputting the entropy slice header and the plurality of entropy encoded syntax element values.

A system is disclosed for selectively applying a paraphrase alternation pattern to a textual input. The system includes a pattern identification component for processing a collection of data and identifying a plurality of potentially applicable paraphrase alternation patterns. A context model provides an objective frame of reference in which to compare one or more of the plurality of potentially applicable paraphrase alternation patterns to the textual input to determine whether the pattern can be applied without changing meaning. A language model provides a principled basis for determining the boundaries of the text segment to be modified.

A method and apparatus for adaptively selecting a context model for entropy coding and a video decoder are provided. A method of coding a residual prediction flag indicating whether residual data for an enhancement layer block of a multi-layered video signal is predicted from residual data for a lower layer block corresponding to the residual data for the enhancement layer block includes the steps of calculating the energy of the residual data for the lower layer block, determining a coding method for the residual prediction flag according to the energy, and coding the residual prediction flag using the determined coding method.

Security is enhanced for a user of a mobile device by monitoring and controlling resource usage. Usage information associated with a mobile device is collected. The collected information is used to build a usage model for a user of the mobile device that describes a set of contexts in which the mobile device is used. User activity on the device is monitored and the model is consulted to determine a first time after which it will be acceptable for a battery of the mobile device to fall below a threshold charge level. Based on the monitored activity, a prediction of a second time is made for when the battery will fall below the threshold charge level. If the second time is before or a predetermined amount of time before the first time, usage of the battery is reduced, else, usage of the battery is not reduced.

The present invention is a system and method for lossless compression of data. The invention consists of a neural network data compression comprised of N levels of neural network using a weighted average of N pattern-level predictors. This new concept uses context mixing algorithms combined with network learning algorithm models. The invention replaces the PPM predictor, which matches the context of the last few characters to previous occurrences in the input, with an N-layer neural network trained by back propagation to assign pattern probabilities when given the context as input. The N-layer network described below, learns and predicts in a single pass, and compresses a similar quantity of patterns according to their adaptive context models generated in real-time. The context flexibility of the present invention ensures that the described system and method is suited for compressing any type of data, including inputs of combinations of different data types.

A method for encoding a syntax element contained in a precoded video signal into a coded bit stream, the precoded video signal representing at least one video frame, the syntax element being associated with a predetermined portion of the video frame and being indicative of as to whether the predetermined portion of the video frame is precoded in a first or a second way into the precoded video signal is described. The method comprises investigating as to whether a neighboring portion of the video frame neighboring the predetermined portion is precoded in the first way or the second way, in order to obtain a binary value; assigning one of at least two context models to the predetermined portion of the video frame based on the binary value, wherein each context model is associated with a different probability estimation; and arithmetically encoding the syntax element into the coded bit stream based on the probability estimation with which the assigned context model is associated.

Methods and apparatuses are provided for adaptive entropy encoding and adaptive entropy decoding using various context models. A scalable entropy encoding method includes determining a context by referring to both syntax elements in the same layer as a block including a syntax element to be encoded and syntax elements in lower layers or only the syntax elements in the lower layers and performing entropy encoding on the syntax element using the determined context.

A solution for generating a Service-Oriented Architecture (SOA) policy based on a context model is provided, which generates an application scope of the SOA policy; generates a context model; generates an action list for the context model based on action semantic modules customized by a user; generates a condition part of the SOA policy according to the context module; generates an action part of the SOA policy according to the action list; and combines the condition part and the action part to generate the SOA policy.

A method detects events in multimedia. Features are extracted from the multimedia. The features are sampled using a sliding window to obtain samples. A context model is constructed for each sample. The context models form a time series. An affinity matrix is determined from the time series models and a commutative distance metric between each pair of context models. A second generalized eigenvector is determined for the affinity matrix, and the samples are then clustered into events according to the second generalized eigenvector.

A method and device for decoding bin values using a pipeline architecture in a CABAC decoder are provided. The method includes reading a first context model required to decode a first bin value, from a memory; determining whether a second context model required to decode a second bin value is the same as the first context model, while decoding the first bin value using the first context model; determining whether a third context model required to decode a third bin value is the same as the second context model, while decoding the second bin value using the second context model, if it is determined that the second context model is the same as the first context model; and reading the second context model from the memory, if it is determined that the second context model is not the same as the first context model.

The present invention relates to, for example, an encoding apparatus and an encoding method, a decoding apparatus and a decoding method, a recording medium, and a program suitable for encoding image signals with a higher compression ratio for transmission or accumulation. In an arithmetic coding section (58), from among the syntax elements of input image compression information, the frame/field flag is first encoded by a frame/field flag context model (91). When the macroblock to be processed is subjected to frame-based encoding, a frame-based context model (92), specified in the current H.26L standard, is applied. On the other hand, when the macroblock to be processed is subjected to field-based encoding, a field-based context model (94) is applied for the syntax elements described below. The present invention is applied to an encoder for encoding image information and a decoder for decoding image information.

A system and method for the improved compression of audio signals and the restoration and enhancement of audio recordings missing high frequency content. In the preferred embodiment the different context models are applied to increase the compression ratio of spectral information, quantization coefficients and other information. Context models and arithmetic compression are used for final compression. The time-frequency amplitude envelope and degree of tonality parameters are extracted from the low frequency component. An estimate of the high frequency component is performed by applying a multiband distortion effect, waveshaping, to the low frequency content. Control of tonality is achieved by varying the number of bands within the multiband framework. A filterbank is used that roughly shapes the reconstructed high frequency component according to an estimation of the most probable shape.

Methods and apparatus for a recommendation system based on collaborative filtering is provided. Explicit and implicit ratings of items by network users are used to create a contextual model. The explicit ratings comprise different rating types regarding different item attributes. The implicit ratings comprise different rating types derived from different user events and may include recency, intensity, or frequency ratings. The contextual model may be optimized for a specific objective function, such as click-through-rate or conversion rate. In other embodiments, item information is used to produce a content model where item information for an item is encoded as metadata into a document that represents the item. The contextual or content model is used to recommend one or more items to a current user. The basic unit of the recommendation system may be an item set of two or more items or a particular sequence of two or more items.

The method includes following steps: scanning DCT coefficient blocks according to sequence so as to obtain last one nonzero coefficient (NC) and the coefficient in front of the last one NC in coefficient block, and number value of NC; based on the number value of NC to calculate difference value between number value of NC in this block and number value of NC in adjacent block, and constructing context model for number value of NC; calculating flag bit of NC for last one NC and coefficients before the last one NC; selecting context model to encode flag bit of NC; subtracting 1 from absolute value of NC according to scanning sequence or scanning inverted sequence; and selecting context model to encode number value of NC, and its position in the scan etc; encoding sign bit. The invention also discloses corresponding decoding method.

A speech recognition system, method of recognizing speech and a computer program product therefor. A client device identified with a context for an associated user selectively streams audio to a provider computer, e.g., a cloud computer. Speech recognition receives streaming audio, maps utterances to specific textual candidates and determines a likelihood of a correct match for each mapped textual candidate. A context model selectively winnows candidate to resolve recognition ambiguity according to context whenever multiple textual candidates are recognized as potential matches for the same mapped utterance. Matches are used to update the context model, which may be used for multiple users in the same context.

There is disclosed a method including receiving sensor data extracted from one or more physical sensors, using the extracted sensor data and a context model to perform a first level context determination, and examining the at least one condition. If the examining indicated that the at least one condition was fulfilled, the context model is adapted on the basis of the sensor data, otherwise adaptation data formed on the basis of the sensor data is provided to a second level context determination. A corresponding apparatus and computer program product are also provided.

A method and apparatus for encoding and decoding an image are provided. The method includes selecting a context model by referring to previously encoded pixels that are adjacent to the current pixel for entropy-encoding a binary value of a pixel value of the current pixel, and entropy-encoding the binary value using the selected context model, thereby performing entropy-coding with high compression efficiency.

Context-based adaptive arithmetic coding and decoding methods and apparatuses with improved coding efficiency using the same are provided. The context-based adaptive arithmetic coding method includes resetting a context model for the given slice to a context model for a slice coded temporally before the given slice, arithmetically encoding a data symbol of the given slice using the reset context model, and updating the context model using a value of the data symbol. The context-based adaptive arithmetic decoding method includes resetting a context model for the given slice to a context model coded temporally before the given slice, arithmetically decoding a bitstream corresponding to the given slice using the reset context model to generate a data symbol of the given slice, and updating the context model using a value of the data symbol.